Apparatus and method for analyzing relative outward flow characterizations of fabricated features

ABSTRACT

An apparatus and method for characterizing gas flow through features fabricated in a hollow part. A pressure regulated cooled gas is applied to an interior of the part to the features fabricated in the part. At the same time, a pressure regulated heated gas is applied to an exterior part skin; and the heated gas has a controlled temperature differential from the pressure regulated cooled gas applied to the part interior. An infrared signature of escaping gas and the surrounding part skin is analyzed by a classification method to identify acceptable and unacceptable fabricated features.

CROSS REFERENCE TO RELATED APPLICATION

This application is a divisional of U.S. patent application Ser. No.12/034,761 filed Feb. 21, 2008 entitled “Apparatus and Method ForAnalyzing Relative Outward Flow Characterizations of FabricatedFeatures”, which is fully incorporated herein. U.S. patent applicationSer. No. 12/034,761 is a continuation-in-part of U.S. patent applicationSer. No. 11/424,084 filed Jun. 14, 2006, now U.S. Pat. No. 7,388,204,which issued on Jun. 17, 2008, which is also fully incorporated byreference herein.

FIELD

The present invention relates to manufacturing gas turbine enginecomponents and, more particularly, to inspecting complex cooling holesthrough a surface of a gas turbine engine component.

BACKGROUND

During operation, gas turbine engines, whether used for flight orstationary power generation, develop extremely high temperature and highvelocity gases in a combustor portion of the engine. These gases areducted on blades of a turbine rotor to cause rotation of the rotor andare redirected by the stator vanes onto additional rotor blades toproduce more work. Because of the high heat of the gases, it isdesirable to cool the blades and vanes to prevent damage and, to extendthe useful life of, these engine components. It is known in the art thata turbine component such as that shown in FIG. 16 can be cooled by filmcooling that is provided by a plurality of fabricated features, forexample, cooling holes.

A commonly used method of cooling a turbine component 20 is to ductcooling air through internal cavities or passages and then vent thecooling air through a plurality of cooling holes 22. This air coolsinternal surfaces of the component by convection and cools thecomponents outer surfaces by film cooling. The cooling holes 22 aretypically formed along a line generally parallel to, and a selecteddistance from, a trailing edge 24 of the component to provide a film ofcooling air over a surface of the component when the cooling holesdischarge air during engine operation. Other rows or arrays of coolingholes or vents may be formed in the blade and vane components of a rotoror stator of a turbine depending upon design constraints.

To facilitate the distribution of the cooling air substantiallycompletely over the convex and concave surfaces of the blade airfoil orplatform, as shown in FIG. 17, the upstream end of each cooling hole 22has a generally cylindrical, inlet portion 26 that extends from alocation 28 inside of a wall of the component 20. At the location 28,the cooling hole 22 then flares or diverges to provide a dischargeportion 30 that terminates on an exterior surface 32 of the component 20to be cooled by the air flow. The shape of the discharge end functionsas a diffuser to reduce the velocity of the cooling airstreams beingdischarged from the cooling holes 22. The lower velocity coolingairstreams are more inclined to cling to the surface 32 for improvedcooling. High quality cooling holes 22 with diffusers 30 providesuperior performance but are costly and difficult to manufacture.

After the cooling holes have been manufactured, it is necessary toinspect each of the holes to determine whether it exists and is properlyformed as a complex hole. One method of inspection is a manual method inwhich an inspector is provided with a drawing of the desired holepattern and a pin. The inspector first confirms that a hole exists ateach location identified by the pattern; and then, the inspector insertsthe pin through each of the holes to determine whether the hole isproperly drilled as a through-hole. As can be appreciated, such aninspection process is highly repetitive, tedious and stressful for theinspector and, in addition, is expensive and inefficient for themanufacturer of the turbine component.

Other known hole inspection processes are automated and utilize a laseror a flow of fluid through the holes. The flowing fluid used mostcommonly is either air or water. In the case of air, the mass of airflowing through a feature can be measured. With water, a visual signalof a flow pattern is possible. These methods need a human visual checkor physical measurement of a single feature to characterize its flowcondition. All of these known methods are time-consuming and rely onhuman intervention to perform the characterization which leads toerrors.

Thus, there is a need for an inspection apparatus and process that canautomatically inspect and identify qualitative characteristics ofcomplex cooling features in gas turbine components faster, moreprecisely and less expensively than known inspection apparatus andprocesses.

SUMMARY

The present invention provides an inspection apparatus and process thataccurately and quickly determine the flow characteristics of coolingfeatures fabricated in gas turbine blades. With the inspection apparatusand process of the present invention, the flow characteristics are easyto interpret; and thus, the inspection apparatus and process are faster,more error-free and less expensive than known tactile and visualinspection processes. The inspection apparatus of the present inventionprovides an automatic process and thus, removes the chance of humanerror. Therefore, the inspection apparatus of the present invention isespecially useful for inspecting a presence and quality of a largenumber of complex cooling holes in gas turbine component.

In a first embodiment, an apparatus for inspecting features extendingfrom a cavity within a structure to an outer surface of the structurehas a thermal imaging device with a lens. A positioning system supportsthe thermal imaging device and is operable to position the lens at adesired position and orientation with respect to one of the features. Aheating component is also supported by the positioning system and isoperable to heat the outer surface around the one of the features. Aflow controller is connected to a first source of gas and operable tosupply a pressure regulated flow of gas, and a chiller receives thepressure regulated flow of gas and provides a pressure regulated flow ofcooled gas into the cavity and to the one of the features. Aprogrammable control is in electrical communications with the thermalimaging device, the positioning system, the heating component, the flowcontroller and the chiller. The programmable control is operable tofirst, heat the outer surface around the one of the features, andthereafter, cause the pressure regulated of cooled gas to flow into thecavity. The programmable control is further operable to cause thethermal imaging device to capture and save thermal images of the outersurface including the one of the features. In different aspects of thisembodiment, the heating component may heat by thermal radiation and/orthermal convection.

Another embodiment is a method of inspecting features extending from acavity within a structure to an outer surface of the structure firstpositions a thermal imaging device at a desired position and orientationwith respect to one of the features. The area of the outer surfaceincluding the one of the features is heated; and thereafter, a pressureregulated flow of a cooled gas is provided to the cavity to the one ofthe features. A first thermal image of the area of the outer surfaceincluding the one of the features is captured and stored. The pressureregulated flow of the cooled gas is terminated, and the above process isrepeated for others of the features. In different aspects of thisembodiment, multiple first thermal images may be captured at differenttimes during the flow of the cooled gas. Further, multiple secondthermal images of the area of the outer surface may be captured andsaved at different times during the heating of the area of the outersurface.

A still further embodiment is a method of inspecting a plurality offeatures extending from a cavity within a structure to an outer surfaceof the structure by analyzing saved thermal images of an area of theouter surface including the plurality of features. The thermal imageswere captured and saved at different times in response to first, heatingthe area of the surface, and thereafter, providing a cooled gas into thecavity and to the plurality of features. The method first identifies afirst thermal image captured after providing the cooled gas into thecavity. The first thermal image is an array of pixels of the area of thesurface including the plurality of features, wherein each pixelrepresents a temperature. A plurality of standard deviations oftemperatures is determined, wherein each of the plurality of standarddeviations is determined by temperatures represented by pixels within aboundary of a different one of the features. An average of the pluralityof standard deviations of temperatures is determined, and a thresholdtemperature using the average of the plurality of standard deviations oftemperatures is determined. A minimum temperature represented by pixelsin the difference array within boundaries of respective ones of theplurality of features is determined. Thereafter, a number of significantpixels within the boundary of one of the features is identified. Eachsignificant pixel represents a temperature less than a sum of thethreshold temperature plus the minimum temperature, and the number ofsignificant pixels represents an area of the one of the featuresallowing a desired flow of the cooled gas. The one of the features isidentified as a good feature in response to the number of significantpixels being greater than a predetermined number, and the above processis iterated for each of the plurality of features.

Yet another embodiment is a method of inspecting a plurality of featuresextending from a cavity within a structure to an outer surface of thestructure by analyzing saved thermal images of an area of the outersurface including the plurality of features. The thermal images werecaptured and saved at different times in response to first, heating thearea of the surface, and thereafter, providing a cooled gas into thecavity and to the plurality of features. A first thermal image and asecond thermal image are captured after providing the cooled gas intothe cavity. The second thermal image was captured later in time than thefirst thermal image. The first and the second thermal images arerespective arrays of pixels of an area of the outer surface thatincludes the plurality of features, wherein each pixel represents atemperature. A plurality of first standard deviations of temperatures isdetermined, wherein each of the plurality of first standard deviationsis represented by pixels within a boundary of a different one of thefeatures in the first thermal image. A plurality of second standarddeviations of temperatures is determined, wherein each of the pluralityof second standard deviations is represented by pixels within a boundaryof a different one of the features in the second thermal image. Afeature is identified as being blocked in response to temperaturesrepresented by pixels within a boundary of the feature in the secondthermal image not being lower than temperatures represented by pixelswithin a corresponding boundary of the feature in the first thermalimage. A feature in the second thermal image is identified as being goodin response to a number of significant pixels within a boundary of thefeature representing temperatures lower than surrounding pixels withinthe boundary of the feature.

A further embodiment of the invention is a method of inspecting aplurality of features extending from a cavity within a structure to anouter surface of the structure by analyzing saved thermal images of anarea of the outer surface including the plurality of features. Thethermal images were captured and saved at different times in response tofirst, heating the area of the surface, and thereafter, providing acooled gas into the cavity and to the plurality of features. Identifyinga first thermal image that was captured before providing the cooled gasinto the cavity and a second thermal image that was captured afterproviding the cooled gas into the cavity. The first and the secondthermal images are respective arrays of pixels of an area of the outersurface that includes the plurality of features, wherein each pixelrepresents a temperature. A difference array of pixels is created,wherein each difference array pixel element equals a difference intemperature between corresponding pixel elements of the first thermalimage and the second thermal image. A plurality of standard deviationsof temperatures is determined using pixels in the difference array,wherein each of the plurality of first standard deviations is determinedby temperatures represented by pixels within a boundary of a differentone of the features. An average of the plurality of standard deviationsof temperatures is determined as is a threshold temperature using theaverage of the plurality of standard deviations of temperatures. Aminimum temperature represented by pixels in the difference array withinboundaries of respective ones of the plurality of features isdetermined. A number of significant pixels within a boundary of afeature is determined, wherein each significant pixel represents atemperature less than a sum of the threshold temperature plus theminimum temperature. The number of significant pixels represents an areaof the feature allowing a desired flow of the cooled gas. The feature isidentified as a good feature in response to the number of significantpixels being greater than a predetermined number.

These and other objects and advantages of the present invention willbecome more readily apparent during the following detailed descriptiontaken in conjunction with the drawings herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a perspective view of an exemplary embodiment of an automatedinspection system for inspecting a complex feature fabricated in a part

FIG. 2 is an overall schematic diagram of a first exemplary embodimentof the automated inspection system shown in FIG. 1.

FIG. 2A is a cross-sectional view of an exemplary embodiment of anannular gas discharge nozzle.

FIG. 3 is a flowchart of an exemplary embodiment of a process foranalyzing a raw infrared image using the embodiments of FIGS. 1, 2 and7.

FIG. 4 is an exemplary representation of a point summing cross patternused in a significant point algorithm with the process shown in FIG. 3.

FIG. 5 is a representation of eight-border coordinates used to determinea feature using the process of FIG. 3.

FIG. 6A is a representation of an image of infrared signatures for thegroup of features shown in FIGS. 1 and 2 when processed according to theprocess shown in FIG. 3.

FIG. 6B is a representation of an image of infrared signatures for agroup of features using a data acquisition method of FIG. 10 and a dataanalysis method, for example, as shown and described with respect toFIGS. 11, 14 and 15.

FIG. 7 is an overall schematic diagram of another exemplary embodimentof the automated inspection system of FIG. 1.

FIG. 8 is a front elevation view of an IR camera lens illustrating andarray of IR emitters and gas discharge nozzles.

FIG. 9 is an overall schematic diagram of a further exemplary embodimentof the automated inspection system of FIG. 1.

FIG. 10 is a flowchart of an exemplary embodiment of an alternative dataacquisition method.

FIG. 11 is a flowchart of an exemplary embodiment of one alternativeprocess for identifying acquired thermal images to be analyzed anddetermining a status of features within the acquired thermal images.

FIG. 12 is a flowchart of an exemplary embodiment of a process fordetermining a standard deviation of detected temperatures inside afeature of the part being inspected.

FIG. 13 is a flowchart of an exemplary embodiment of a process foranalyzing temperatures detected in a feature of the part beinginspected.

FIG. 14 is a flowchart of an exemplary embodiment of a furtheralternative process for identifying acquired thermal images to beanalyzed and determining a status of features within the acquiredthermal images.

FIG. 15 is a flowchart of an exemplary embodiment of yet anotheralternative process for identifying acquired thermal images to beanalyzed and determining a status of features within the acquiredthermal images.

FIG. 16 is a partial perspective view of an example of a known turbinecomponent that utilizes rows of features or cooling holes that must beinspected using the embodiments described herein.

FIG. 17 is a partial perspective and cross-sectional view of a coolinghole in the turbine component illustrated in FIG. 16.

DETAILED DESCRIPTION

Referring to FIGS. 1 and 2, one example of a feature inspection system38 is used to inspect fabricated features in a part, for example, aircooling holes 22 in a known turbine blade 20 as described with respectto FIGS. 8 and 9. The blade 20 is supported in a holding fixture 40; anda gas tight seal 42, for example, a molded urethane seal, is formedaround an inlet opening at a base 44 of the blade 20. A robotic arm 46is mounted in a cabinet 27 and is controlled by a programmable control48 also mounted on the cabinet 27. The robotic arm 46 is operable toposition a thermal imaging device, for example, an infrared (IR)radiometer or camera 50, with respect to the blade 20. In one exemplaryembodiment, the robotic arm 46 is mounted upside-down above the blade20, so that the robotic arm 46 can be moved to different positions andorientations that permit the IR camera 50 to provide thermal images ofall of the fabricated blade features 22 to be inspected. For purposes ofthis document, a position refers to a point, for example, a center pointof the IR camera lens 51, that is located with respect to a threedimensional linear coordinate system, for example, an x, y, z position.Orientation refers to a placement of the IR camera lens centerline 100(FIG. 2A) in a desired direction with respect to the outer surface 79.The robotic arm 46 may be one of several commercially available six-axesrobot arms, for example, a six-axes robot arm commercially availablefrom DENSO Robotics of Long Beach, Calif. The IR camera 50 is anuncooled IR detector array consisting of 76,800 micro bolometer elementsarranged in a pattern that is 320 elements wide by 240 elements high.The IR camera 50 is capable of detecting electromagnetic energy in therange of 7.5-13 micrometers and may be one of several commerciallyavailable cameras such as those available from FLIR Systems, Inc. ofWilsonville, Oreg.

In a feature inspection cycle, the IR camera 50 is positioned at adesired position and orientation with respect to the blade; and thecontrol 48 commands a first valve 64 to open, which allows air from asource of pressurized air 66 to enter a heater 68. The source ofpressurized air provides clean air, for example, air with an air dewpoint no greater than +30 F, no particulate size greater than 1 micronand an oil content less than 10 PPM weights.

The control 48 is also electrically connected to the heater 68 and afirst temperature sensor 70 providing a first temperature feedbacksignal. The control 48 uses the first temperature feedback signal and aknown PID control to operate the heater 68 and bring the air temperatureto a range of about 70-315 degrees Fahrenheit. A first gas pressureregulator 72 is electrically connected to, and operable by, the control48 to provide the air at a pressure in a range of about 0.05-3.0pound(s) per square inch gauge (“PSIG”), thereby providing a desiredflow of the warmer first gas. This warmer air passes through a nozzle 76and is applied over an area of a blade outer surface or skin 79 thatsurrounds the various features 22 being inspected. The nozzle 76 maysimply be an open end of a tube positioned adjacent the camera lens 51and directed toward one or more features being captured by the IR camera50. In an alternative exemplary embodiment shown in FIG. 2A, the nozzle76 may be an annular piece or ring 94 sized to be mounted around an IRcamera lens 51. An annular gas passage 96 intersects a number of angledgas discharge passages 98 located circumferentially around the annularpiece 94 and hence, the IR camera lens 51. The gas discharge passages 98may be angled to intersect a centerline 100 at generally a common point102, and thus, the discharge passages 98 are angled or directed towardthe one or more features to be captured by the IR camera 50. As will beappreciated, in other embodiments, the nozzle 76 may alternatively beone or more devices that are attached to the robotic arm 46 andoperative to direct a gas over a portion of the surface 79 that is atarget area of the IR camera 50.

Simultaneously with opening the first valve 64, the control 48 commandsa second valve 52 to open, which allows a helium gas from a source ofhelium gas 54 to enter a chiller 56. The control 48 is also electricallyconnected to the chiller 56 and a second temperature sensor 58 providinga second temperature feedback signal. The control 48 uses the secondtemperature feedback signal and a known PID control to operate thechiller 56 and bring the air to a temperature in a range of about 25-70degrees Fahrenheit. A second gas pressure regulator 60 is electricallyconnected to, and operable by, the control 48 to maintain the helium ata pressure in a range of about 0.1-35 PSIG, thereby providing a desiredflow of the cooler second gas. The chilled and pressurized helium gas isthen applied through the fixture 40 and into an interior cavity throughan opening at the base 44 of the blade 20 and allowed to escape throughthe various features 22 that are being inspected.

An initial pre-inspection cycle in a range of about 1-30 seconds is usedto purge air from an interior of the blade 20, and the blade 20 isbrought to a desired temperature. A control memory 78 stores a holeinspection application program 92 that is operable to inspect the bladefeatures 22 with the IR camera 50 and analyze detected temperatures toidentify a feature present, partial feature present or an absence of afeature. An exemplary embodiment of one process of the inspection cycleprogram 92 for acquiring data relating to features of the part andanalyzing that data is shown in FIG. 3. Referring to FIG. 3, the control48 first, at 300, commands the robotic arm 46 to move the IR camera 50to a first position and orientation with respect to the blade 20. The IRcamera 50 is operated by the control 48 to capture a raw image in an X-Ypattern. The X-Y pattern is an array or grid of 320 temperatures in theX-axis and 240 temperatures in the Y-axis, for total of 76,800floating-point temperatures. In this exemplary embodiment, the IR camera50 is operable to convert the X-Y temperature grid pattern tocorresponding digital signals and store them in memory 78.

The control 48 then, at 302, commands a transfer of the temperature gridpattern from the IR camera 50 to the control memory 78, thereby endingthe first data acquisition portion of the inspection cycle program ofFIG. 3. Next, the inspection cycle program initiates an exemplary firstdata analysis method. At 304, the entire temperature grid pattern isfirst analyzed to locate a first region of interest. As willsubsequently be described, a region of interest is one or more of thefeatures 22 that have been previously identified in a setup cycle.Therefore, for each programmed IR camera position, one or more regionsof interest are stored in the memory 78; and a region can be imposed on,or identified within, the stored X-Y temperature grid pattern.

Thereafter, at 306, a “significant point” detection process beginswithin a chosen region of interest; and the significant point detectionprocess is used to analyze each X-Y temperature point in the gridpattern of a region of interest. The analysis of each X-Y temperaturepoint begins by summing a first X-Y temperature point with pointsdirectly next to it in a first cross pattern to determine an averagetemperature. A cross pattern size, that is, the number of points to besummed in the four directions from the first point, is determined by aselected target size setting of even numbers in a range of about 2-20points. The cross pattern size is chosen during the setup cycle as willbe described. An example of a point summing cross pattern is shown inFIG. 4. If the temperature point 23 being analyzed and the selectedtarget size are two, then an average value of the temperature points23-23 h is determined using Equation 1 below. Equation 1 is a generalmathematical expression or algorithm for determining an averagetemperature in the first cross pattern, and its result is used as a holearea temperature baseline.

$\begin{matrix}{\overset{\_}{hole} = \frac{{\sum\limits_{i = {n - \frac{t_{s}}{2}}}^{i = {n + \frac{t_{s}}{2}}}\;{X_{i}Y_{n}}} + {\sum\limits_{i = {n - \frac{t_{s}}{2}}}^{i = {n + \frac{t_{s}}{2}}}\;{X_{n}Y_{i}}}}{{2\; t_{s}} + 2}} & ( {{Eq}.\mspace{14mu} 1} )\end{matrix}$Where

t_(s)=target size setting

n=temperature array index

Next, as further shown in FIG. 4, X-Y temperature points in a secondcross pattern beyond the first cross pattern are used in a similarfashion to determine temperature baseline of the surrounding skin area79. The skin area region represented by a second cross pattern size isalso defined by a target size setting of even numbers in a range ofabout 2-20 points. Continuing with the above example in FIG. 4, for thetemperature point 23, if the selected target size is two, then anaverage value of the temperature points 25 a-25 h is determined usingEquation 2 below. Equation 2 is a general mathematical expression oralgorithm for determining an average temperature in the second crosspattern beyond the first cross pattern, and its result is used as a skinarea temperature baseline.

$\begin{matrix}{\overset{\_}{skin} = \frac{\begin{matrix}{{\sum\limits_{i = {n - t_{s}}}^{i = {n - \frac{t_{s}}{2} - 1}}{X_{i}Y_{n}}} + {\sum\limits_{i = {n + \frac{t_{s}}{2} + 1}}^{i = {n + t_{s}}}\;{X_{i}Y_{n}}} +} \\{{\sum\limits_{i = {n - t_{s}}}^{i = {n - \frac{t_{s}}{2} - 1}}{X_{n}Y_{i}}} + {\sum\limits_{i = {n + \frac{t_{s}}{2} + 1}}^{i = {n + t_{s}}}{X_{n}Y_{i}}}}\end{matrix}}{2\; t_{s}}} & {{Eq}.\mspace{14mu} 2}\end{matrix}$Where

t_(s)=target size setting

n=temperature array index

Thereafter, a difference between the average skin and hole temperaturesis determined using Equation 3a below and compared to a selectablethreshold setting in a range of about 0.01-10.Δtemp= skin− hole  (Eq. 3a)If the temperature difference between the average skin and holetemperatures is determined to be less than a selected temperaturethreshold or reference value, then the Xn-Yn temperature point beinganalyzed is considered not to be significant. In the example of FIG. 4,if the temperature difference using the temperature point 23 is lessthan the temperature threshold, the temperature point 23 is notconsidered to be associated with a blade feature 22. The process thenrepeats the above analysis with the next X-Y temperature point in theX-Y temperature grid.

However, if the average skin and hole temperatures of any X-Ytemperature point is greater than the temperature threshold, that X-Ytemperature point is considered to represent a temperature pointassociated with a feature and is stored in the memory 78 as asignificant point in an array of significant points. The above processis repeated for all of the points in the region of interest, and theoutput of this algorithm is an array of significant points. Thetemperature threshold or reference temperature is determined during thesetup process.

The control 48 is operable, at 308, to identify the various features bydetecting all significant points that share a common border. If asignificant point is bordered by another significant point, these pointsare grouped to form a detected feature. The algorithm used for detectionis an eight cell test as shown in FIG. 5. For a selected significantpoint, each of the coordinates for the eight bordering points is testedfor its existence in the array of significant points. Bordering pointsthat are found are deleted from the significant point array and storedalong with an associated center point as a detected feature in a featurearray in the memory 78. This process continues until no furtherbordering points are found. Thus, each feature identified in the featurearray is defined by a center point and eight bordering points. Thecontrol 48 repeats the above process until all significant points havebeen tested.

The center coordinates of each detected feature are determined by thecontrol 48, at 310, using Equations 4 and 5 below. The X center pointdetermined by Equation 4 and the Y center point determined by Equation 5are each found by dividing a sum of all respective axis points by anarea value and adding one as a bias. This area value, A, is used forclassification of the feature.

$\begin{matrix}{X_{center} = {\frac{\sum\limits^{\;}\; X}{A} + 1}} & ( {{Eq}.\mspace{14mu} 4} ) \\{Y_{center} = {\frac{\sum\limits^{\;}\; Y}{A} + 1}} & ( {{Eq}.\mspace{14mu} 5} )\end{matrix}$

Next, the control 48 determines, at 312, a classification or qualitativecharacteristic of a detected feature using Equations 6 and 7 below.First, with Equation 6, a comparison of the detected feature area, A, ismade with a stored selected partial limit size. If a feature area isgreater than or equal to a selected partial limit size, which is in arange of about 1-50 points, the feature is classified as a through hole82 shown in FIG. 6A; however, if the feature area is less than thepartial limit size, the feature is classified as a partially blockedhole 84. The partial limit size is selected during the setup cycle.Using Equation 7, blocked holes 80 are determined by calculating adifference between an expected number of holes and a total number ofholes detected. Extra holes are indicated to by a negative result ofEquation 7.A=Σfeature_points  (Eq. 6)E=expected_features−no_features_found  (Eq. 7)

Thereafter, the control 48, at 314, determines whether all detectedfeatures in the feature array have been classified. If not, theclassification process described above is repeated until all features inthe feature array have been classified. Next, the control 48 determines,at 316, whether the current position and orientation of the IR camera isthe last position and orientation. If not, the process of FIG. 3 isrepeated until the IR camera 50 has been moved to all of the positionsand orientations stored in the memory 78 and thus inspecting andclassifying all of the blade features 22.

In order to establish desired positions and orientations for the IRcamera 50 and determine values for many of the parameters used inexecuting the inspection cycle program 92 of FIG. 3, a setup cycleprocess is executed. In a first step of the setup cycle, the robotic arm46 is moved to various preliminary positions around the blade 20 by anoperator providing input commands to the control 48. At each preliminaryposition, an IR setup image is taken and stored in the computer 48; anda sufficient number of preliminary positions are chosen, so that all ofthe blade features 22 to be inspected are in one or more setup images.Further, to provide the most reliable feature discrimination, at each ofthe preliminary positions, the IR camera 50 is oriented such that thecenterline of the lens 51 is generally parallel to a centerline of thefeatures or holes 22 to be inspected. However, the feature inspectionsystems and processes described herein are operable with other IR cameraorientations.

Next, for convenience, often the setup images are transferred to acomputer remote from the control 48 of the inspection system 38 in orderto finish the setup process. Such a remote computer is loaded with theinspection cycle program of FIG. 3 and is able to operate the inspectioncycle program in a simulation mode. Further, the user is able to createa display of each of the setup images using a known program thatconverts the X-Y temperature point grid pattern of each image to a coloror gray scale. Upon viewing each image, the user determines which, ifany, features are best shown in that image. In that viewing process, theinspection cycle program of FIG. 3 is executed using default values forsetup selectable parameters, for example, the target size setting, thetemperature array index, the temperature threshold, the partial limitsize and other parameters.

The user is able to change the values of those parameters and observehow the result of the inspection cycle program changes in terms of beingable to better discriminate, identify and classify one or more featuresof interest. The results of the inspection cycle program are displayedto the user in a manner similar to the view shown in FIG. 6A. Thus, forexample, during the simulation, the user can increase the target sizesetting to see if that impacts the resulting discrimination andclassification. Further, the gas temperatures can be changed to increasethe resulting temperature difference determined in Equation 3. Often thelarger the temperature difference the better the discrimination and thefaster the feature inspection process can be executed. However, gastemperatures that are too high or too low will affect featurediscrimination, so there must a balance struck between a temperaturedifference and the gas temperatures.

If the user is not satisfied with the result of the simulation of theinspection cycle program, the setup image can be deleted; and the nextsetup image viewed. If the user is satisfied with the resulting featureclassification of the inspection cycle program simulation, the userplaces a boundary around one or more of the features being observed, forexample, the region of interest boundary 86 of FIG. 6A. That boundaryrepresents a region of interest in a setup image taken at a particularpreliminary position and orientation. In any setup image, the user cancreate as many boundaries or regions of interest as there are holes; andeach region of interest can include one or more holes or rows of holes.Further, that particular preliminary position and orientation is definedas a programmed position and orientation that are to be used duringsubsequent executions of the inspection cycle program either in asimulation mode or during a part inspection cycle or process.

The above process is repeated until all of the features 22 on the blade20 have been inspected in a region of interest. If some features cannotbe adequately defined, then more setup images must be taken; and theabove process repeated for those features. At this point, the inspectioncycle program 92 includes (1) all of the positions and orientations ofthe IR camera 50 that are necessary to inspect the desired bladefeatures 22, (2) all of the regions of interest 86 for a position andorientation, wherein each region of interest defines one or more of theblade features, and (3) values for all of the selectable parameters, forexample, the target size setting, the temperature array index, thetemperature threshold, the partial limit size and other parameters,which have been determined to provide the best feature discrimination.The inspection cycle program is then transferred to the control memory78, and an inspection cycle can be executed.

A pre-inspection cycle is used to normalize the temperature of the blade20. In the pre-inspection cycle, the control 48 opens the valves 64, 52to initiate flows of air and helium. Temperature feedback signals fromthe temperature sensors 70, 58 are used by the control 48 to operate therespective heater 68 and chiller 56 to bring the air and helium to adesired temperature. Further, the flows of cooled helium through theblade 20 and heated air over the blade skin 79 for a period of time, forexample, 1-30 seconds, normalizes the temperature of the blade, that is,the blade temperature reaches a sufficiently stable value to permitexecution of the inspection process.

During the pre-inspection cycle, the control 48 also operates thepressure regulators 72 and 60 to establish desired pressures for theheated air and chilled helium respectively. The desired pressures arechosen during the setup cycle to optimize a discrimination andclassification of features in the IR image during the inspectionprocess. For example, if the air is too cold or the helium is too hot,feature discrimination and classification will be adversely affected.Further, once desired pressures of the air and helium are establishedthat provide an acceptable feature discrimination and classification,changes in the ambient pressure around the blade 20 will adverselyaffect the feature discrimination and classification process. Therefore,during the pre-inspection cycle, a pressure sensor 90 provides thecontrol 48 with a pressure signal representing the ambient pressurearound the blade 20. The control 48 then sets the desired air and heliumpressures as respective multiple values of the ambient air pressure toestablish a desired ratio of air and helium pressures. Further, as theambient pressure changes during subsequent executions of the featureinspection program, the control 48 changes the respective multiplevalues to maintain the desired air and helium pressures in constantrelationship with respect to the ambient air pressure. To determine thedesired air and helium pressures, the robotic arm can be moved todifferent inspection programmed positions; and the IR camera imagesviewed. The air and helium pressures are then adjusted to change the gasflows until an IR image of the desired quality is obtained.

In an alternative exemplary embodiment shown in FIG. 7, an alternative,second data acquisition method of the feature inspection cycle isprovided by inverting the locations of the chiller 56 and the heater 68.With this embodiment, the control 48 operates the first pressureregulator 72 to supply air to the chiller 56 at a pressure in a range ofabout 0.05-3.0 PSIG. The chiller 56 cools the air to a temperature in arange of about 25-70 degrees. This cold air is applied through thenozzle 76 to an outer surface of the blade 20 around the variousfeatures being supplied the heated helium. At the same time, the control48 operates the second pressure regulator 60 to supply the helium gas 54to the heater 68 at a pressure in a range of about 0.1-35 PSIG. Theheater 68 heats the helium gas to a temperature in a range of about70-150 degrees, and the heated helium is applied to an interior cavitythrough an opening at the base 44 of the blade 20 and allowed to escapethrough the various features 22 to be inspected. After a period of time,the IR camera 50 is triggered to capture a temperature image; and theprocess previously described with respect to FIG. 3 is repeated toidentify and classify various features. However, it should be noted thatwith this second data acquisition method, a second data analysis methodis used. An exemplary embodiment of the second data analysis method isidentical to the first data analysis method except that for thesignificant test, instead of using Equation 3a, an Equation 3b is used,which is set forth below:Δtemp= hole− skin,  (Eq. 3b)

The feature inspection systems 38 of FIGS. 1, 2 and 7 and method of FIG.3 are substantially automated, faster, more error-free and lessexpensive than known tactile and visual inspection methods. The featureinspection systems 38 of FIGS. 1, 2 and 7 inject a gas through theinternal passages of the blade 20, which is less dense and lighter thanambient air, for example, helium. The lighter gas provides a morepredictable and reliable gas flow through the small passages within theblade 20 and out the complex shaped features 22 that exit on the bladeskin 79. Further, the feature inspection systems 38 of FIGS. 1, 2 and 7provide a simultaneous heating of one gas, for example, air, and coolingof the other gas, for example, helium. The simultaneous heating andcooling improves the capability of the feature inspection systems 38 todiscriminate and classify features using the process described withrespect to FIG. 3. In addition, the feature inspection systems of FIGS.1, 2 and 7 continuously regulate the pressures of the gas with respectto ambient air pressure around the blade 20. Such a pressure regulationfurther improves the capability of the feature inspection systems 38 todiscriminate and classify the blade features 22. Thus, the featureinspection systems 38 are especially useful for inspecting a largenumber of complex fabricated features, for example, cooling holes, ingas turbine component.

An exemplary embodiment of an alternative, third data acquisition methoduses a programmed delay between the application of the downstream airand upstream air. In practice, the IR camera 50 (FIG. 2) is moved to adesired position and orientation with respect to a feature 22 of theblade 20. The control 48 commands the downstream valve 64 to open, whichflows heated gas or air over the surface 79. After a first programmedperiod of time sufficient to allow the skin temperature of the surface79 to stabilize, the control 48 commands the upstream valve 52 to open.This ports chilled helium through the base 44 of the blade 20 and outthe features 22. After a second programmed period of time, the IR camerais triggered; and a first, single raw IR image is captured. This rawimage is stored in the control's memory at 302 of FIG. 3. The control 48commands the upstream valve 52 to close. The disclosed first dataanalysis method of steps 304-314 of FIG. 3 is executed, and the IRcamera 50 is then moved to the next programmed position. With acontinuous flow of downstream heated air, the above sequence of eventsis repeated to apply bursts of upstream chilled helium until allprogrammed positions have been cycled.

An exemplary embodiment of a variation of the third data acquisitionmethod adds a third programmed period of time that starts after theacquisition of the first, single raw IR image. Upon expiration of thisthird time period, a second, single raw IR image is captured and stored.Thereafter, the control 48 commands the upstream valve 52 to close. Analternative, third data analysis method is then used with this variationof the third data acquisition method. Analysis of the dual IR image isperformed by first creating a difference temperature X-Y array or gridin which the temperature of each array element is created by subtractinga temperature array element in the first raw IR image from acorresponding temperature array element in the second raw IR image. Theresulting temperature difference array is then analyzed using steps 304through 314 of FIG. 3 with the significant test using Equation 3b. Thisdual raw IR image cycle is repeated for all other programmed positions.

An alternative fourth data acquisition method may optionally useinfrared (“IR”) emitters 110 to heat the surface 79 of the blade 20 viathermal radiation. The thermal radiation may be applied either with, orwithout, heating by thermal convection using the downstream hot air.Referring to FIG. 8, with this embodiment, a group of infrared (“IR”)emitters 110 and hot air nozzles 112 are mounted around the IR cameralens 51 in place of the nozzle ring 94 shown in FIG. 2A. The exemplaryembodiment has the IR emitters 110 mounted at 45 degrees. The airnozzles 112 are mounted on a bisecting angle between the infraredemitters. Use of the emitters is most effective when the emissivity ofthe skin is low, that is, more reflective. In one embodiment, theemitters 110 may be IR-12K emitters commercially available from BostonElectronics Corporation of Brookline Mass. Each emitter 110 is mountedinside a PI-224 elliptical reflector with a calcium fluoride window,also available from Boston Electronics.

FIG. 9 illustrates another embodiment of the feature or hole inspectionsystem 38 that is utilized with the fourth data acquisition method. Inthis embodiment, the components that have identical numbers as thecomponents in FIGS. 2 and 7 are substantially similar thereto. Thecontrol 48 has a plurality of controllers 120-128 that may be embodiedin programmable hardware and/or software. The controllers 120-128 may beembodied in separate programmable processors, or one or more of thecontroller functions may be included in a single programmable processor.A particular embodiment of the controllers 120-128 is a matter of designchoice. The operation of the controllers 120-124 is coordinated by amain controller 126 that communicates with the other controllers via anetwork 130, for example, an ethernet. The main controller 126 alsocommunicates with one or more user interfaces 138. A user interface 138often has a monitor 140, a touch screen 142, a mouse 144, a keyboard 146and a bar code reader 148. The user interface 138 may have multiplemonitors and touch screens as well as the other user interfacecomponents.

A part clamp controller 128 has a separate user interface and is capableof independent operation. The part clamp controller 128 is operative inresponse to user commands to clamp the part 20 in the adapter plate 132.The proper loading of the part 20 with respect to the adapter plate 132is checked by a part loaded sensor 134 and adaptor loaded sensor 136,respectively. The states of the sensors 134, 136 are detected by therobot safety controller 122 and communicated to the main controller 126via an interface controller 124. The interface controller 124, inresponse to the main controller 126, provides, in a known manner, analogand digital command signals to, and receives analog and digital feedbacksignals from, devices in the inspection system 38.

In response to commands from the main controller 126, the robot motioncontroller 120 controls, in a known manner, the operation of the robotarm 46 and is operative to position the IR camera 50, which is mountedat the end of the robot arm, at desired positions and orientations withrespect to the part 20. Once the IR camera 50 is in position, the maincontroller 126 may command, via the interface controller 124, aprogrammable power supply 135 to turn on the IR emitters 110 (FIG. 8) ata desired voltage. An emitter feedback voltage signal is provided onsignal line 160 to the interface controller 124. The main controller 126may also provide, via the interface controller 124, a command voltage onsignal line 150 to operate a downstream airflow controller 152, which isoperative to supply a desired flow of air from a source 66 to a heater68. The downstream airflow controller 152 maintains the desired flow ofair by regulating the air pressure. The main controller 126 alsocontrols, via the interface controller 124, the operation of the heater68 and the three-way valve 156 to port the heated, pressure regulatedair flow through the hot air nozzles 112 (FIG. 8).

The main controller 126 may also provide, via the interface controller124, a command voltage on signal line 164 to operate an upstream airflowcontroller 166, which is operative to supply a desired flow of air orhelium from a source 162 to a chiller 56. Again, if the source 162 isair, it is clean air, for example, air with an air dew point no greaterthan +30 F, no particulate size greater than 1 micron and an oil contentless than 10 PPM weights. The upstream airflow controller 166 maintainsthe desired flow by regulating the pressure. The main controller 126also controls, via the interface controller 124, the operation of thechiller 56 to port the chilled, pressure regulated flow through the flowfixture 40. An atmospheric air pressure signal and pressure andtemperature feedback signals for the chilled flow are provided on signalline 168 from the flow fixture 40 to the main controller 126 via theinterface controller 124.

With the fourth data acquisition method, the IR emitters 110 anddownstream heated air may be used separately or together. Further, theupstream fluid may be chilled air or helium. The fourth data acquisitionmethod supports any of those combinations, and depending on a part'semissivity, cooling hole pattern and other physical characteristics, aparticular combination may provide an optimum feature discrimination.Generally, in a preproduction process, different combinations are triedto see which combination provides the best hole or featurediscrimination. The fourth data acquisition method is a furtherextension of the third data acquisition method in that a sequence ofmore than two IR images is captured.

An exemplary embodiment of the fourth data acquisition method is shownin FIG. 10. The control 48 initiates, at 400, a heating of the surface79 of the blade 20 by activating the IR emitters 110 and/or the valve 64to initiate a flow heated downstream air through nozzles 112. Thecontrol 48 then commands, at 402, the robotic arm 46 to move the IRcamera 50 to a first position with respect to one, or a group of, thefeatures. Upon detecting, at 403, that the robotic arm 46 has achievedthe commanded position, the control 48 initializes or zeros two countersat 404. Next, the control 48 then checks, at 406, the upstream fluidpressure to determine whether the upstream chilled gas flow is off. Ifso, the control 48 then captures, at 408, an image from the IR camera 50and associated data and stores the image and associated data in thecontrol memory 78.

This memory storage takes the form of a binary file. The raw IR data isstored as 76,800 floating-point numbers followed by the test metricspresent at the time the IR image was captured. The metrics are stored aspredefined structure composed of, for example, the upstream pressure andtemperature, the downstream pressure and temperature, the barometricpressure; the IR emitter voltage and the date and time.

The control 48 then executes a dwell or time delay at 410 and then, at412, increments counter 1. At 414, the control 48 compares the counter 1value to the time period for the downstream image capture cycle. If thecounter 1 value is less than the downstream image capture time period,the control 48 iterates steps 408-414 to capture further images andassociated data until the counter 1 value exceeds the downstream imagecapture period.

Thereafter, the control 48 turns on, at 416, the upstream chilled gas,for example, air or helium and thereafter, at 418, captures and storesan image and associated data in a manner as described above. The control48 then waits, at 420, for a dwell or time delay; and then incrementscounter 1. At 424, the control 48 determines whether the counter 1 valueis greater than the total of the downstream and the upstream imagecapture time periods. If not, the control 48 then iterates steps 418-424to capture more images. When the counter 1 time value exceeds thedownstream and upstream image capture time periods, the control 48, at426, turns off, the upstream chilled gas and commands, at 428, therobotic arm to move the IR camera to the next position.

The IR emitters 110 and/or downstream heated air directed at the bladesurface 79 remain continuously on during the fourth data acquisitioncycle, and the process of FIG. 10 is repeated to capture images of allof the features 22 on the blade 20. In executing the process of FIG. 10,if the control 48 determines, at 406, that the upstream fluid pressureis too high, it pauses for a period of time as shown by steps 430-434.If the upstream fluid pressure does not reduce over that period of time,the data acquisition cycle is aborted by the control 48 as indicated at436.

A fourth data analysis method is executed after data is acquired at eachposition with the fourth data acquisition method. The fourth dataanalysis method is different in several respects than the data analysismethods described earlier with respect to FIG. 3. For example, thefourth data analysis method is organized into positions and features orholes. A position is the end point of the robot's movement, which isaccurately positioned with respect to a feature or hole of interest(“HOI”) and is where the raw IR images are captured. A particular HOIcan now be identified as a region. By programming the nominal positionof a feature or hole, a nonconforming feature or hole can be moreprecisely identified. Another advantage of the fourth data analysismethod is that the cross-pattern and eight-border algorithms describedwith respect to FIGS. 3 and 4, respectively, are not required.

In the exemplary embodiment of a fourth data analysis method shown inFIG. 11, the control 48 sets, at 450, a flag to a zero or a false stateand a frame counter to zero. The fourth data analysis method looks atthe second image that was captured after the upstream pressure reaches apredetermined level, for example, 0.5 PSIG. This delay provides moretime for the effect of the chilled upstream air to show up in the IRimage. In contrast, the effect of the chilled upstream helium shows upmore quickly. To find that image, the control, at 451, determines thatthe current frame count is not equal to the total number of framesavailable; and thereafter reads the next raw image frame and associateddata. The control 48 then, at 454, increments the frame counter, and, at456, determines from the data whether upstream pressure is active. Ifnot, the control 48 iterates through steps 451-456 until an image isfound with associated data indicating that the upstream pressure greaterthan 0.5 PSIG. Next, a determination is made, at 458, whether the flagis false; and if so, the flag is set true at 460. A subsequent raw imageand data is then read at 452, and this is the second image capturedafter the upstream pressure is activated. The control 48 then saves, at462, the second image and associated data; and, at 464, the image isdisplayed, for example, image 170 shown in FIG. 6B.

The control 48 then, at 466, resets the feature or hole counter to zero,which counts the number of features or holes being analyzed, which, forexample, in FIG. 6B is four holes 174. At 468, the control 48 determinesa standard deviation of the temperatures detected in the HOI in thesaved second IR image. One exemplary embodiment of that process is shownin more detail in FIG. 12. First, at 500, a HOI sum register and pixelnumber counter are set to zero. As noted earlier, an image is an arrayor grid of 76,800 floating point temperatures, which has 320temperatures in the X-axis and 240 temperatures in the Y-axis. Further,the IR image may include several holes, and knowing the position of theend of the robotic arm, the control 48 is able, at 502 and 504, todetermine corner coordinates of an area, for example, area 172 of FIG.6B, which may be slightly larger than, and includes the full area of, aparticular HOI. The HOI of interest may be a square, rectangle,parallelogram or other polygon. Next, the control 48 then retrieves, at506, an area of pixels from the image that are bounded by the cornercoordinates.

Thereafter, at 508, the control 48 starts at one x,y corner coordinateand determines, at 510, whether that x,y coordinate is within the HOI;and if not, the control 48 increments, at 512, to the next x-coordinatewhile holding the same y coordinate. If the next x coordinate is greaterthan the x corner coordinate as determined at 514, the next x,ycoordinate is tested, at 510, as to whether it is inside the HOI. Again,because the control 48 knows the coordinates of the geometry of the HOIwith respect to the image being analyzed, the control 48 can determineif the x,y coordinate is inside the HOI. If it is, the control 48 then,at 516, adds the temperature of that x,y coordinate to the HOI sumregister. The temperature of that x,y coordinate is stored, and thepixel number counter is incremented by one. This process of steps510-516 is repeated for each x coordinate along the first y coordinateuntil the next x corner coordinate is detected at 514.

The y coordinate is incremented, at 518, to the next row in the grid. Atest, at 520, determines whether the new y coordinate is a y cornercoordinate; and if not, the x coordinate is reset at 522. The process ofsteps 510-522 is repeated until every point within the area of thecorner coordinates is tested as to whether it is inside the HOI. At theend of the process, the HOI sum register has a sum of all of thetemperatures inside the HOI; and the temperature of each pixel insidethe HOI is stored. Also, the pixel counter has a count of the number ofpixels inside the HOI. With the above process, the control 48 is able toquickly limit the number of image pixels to be analyzed to only thoseinside a particular HOI within the stored second image. Thereafter, thecontrol 48 determines, at 524, the standard deviation of thetemperatures within the HOI.

Returning to FIG. 11, the standard deviation of the HOI is saved at 470.In this embodiment, only the standard deviation (hoi_stdev) is necessaryto be calculated for each temperature point inside the HOI. However, inpractice, the average temperature and its maximum and minimum are oftenalso determined. The control 48 then increments, at 472, the holecounter and, at 474, determines whether the hole counter is less thanthe total number of holes. If so, steps 468-474 are repeated for otherholes within the stored second image. After the standard deviations forall of the holes have been determined, the control 48 determines, at476, an average of the standard deviations and, at 478, the hole counteris reset to zero.

The control 48 then, at 480, analyses temperatures and classifies eachHOI. One exemplary embodiment of that process is shown in more detail inFIG. 13. First, the control 48 determines, at 550, a threshold value. Inthis embodiment, the value of k is 0.25. Thereafter, the control 48proceeds to execute steps 552-564, which are substantially similar tothe process of steps 502-514 shown and described with respect to FIG.12. First, x,y corner coordinates of an area that is slightly largerthan, but includes the full area of, a particular HOI are determined;and an area of pixels is retrieved from the image that are within anarea bounded by the x,y corner coordinates. The control 48 then tests,at 560, whether a pixel is within the HOI. If it is, at 566, thetemperature of that pixel is saved; and a pixel counter is incremented.The control 48 then determines, at 565, whether the saved pixeltemperature is greater than a current HOI minimum temperature. If not,the saved pixel temperature is set, at 567, as the current HOI minimumtemperature. The control 48 then increments to analyze the next pixel,and the process of steps 560-572 continues in a manner similar to thatpreviously described with respect to process steps 510-522 of FIG. 12.After all of the pixels have been analyzed, all of the temperaturesinside the HOI have been saved; the number of pixels inside the HOI isstored in the pixel counter; and the minimum temperature within the HOIis known. It should be noted that the exemplary embodiments in FIGS. 11and 12 may have some redundancies that may be eliminated in otherembodiments.

The control 48 then resets, at 574, a counter that counts the number ofpixels inside the HOI. Then, the control 48 determines, at 576, whethera saved pixel temperature is greater than the sum of the threshold valueplus the minimum temperature. It should be remembered that the image wascaptured using data acquisition method 4, that is, after the upstreamchilled air was turned on. Therefore, temperatures measured in a goodhole should be lower than surrounding temperatures. If the saved pixeltemperature is less than the sum of the threshold value plus the minimumtemperature, the control 48 sets, at 578, a pixel state as trueidentifying it as a significant point located in the HOI and further,increments a hole area counter by one. If the saved pixel temperature isgreater than the sum of the threshold value plus the minimumtemperature, that means the chilled upstream air is not getting through;and the pixel state is set, at 580, to false, indicating that the pixelrepresents hot skin or a blocked hole and not a through hole. Thecontrol 48 then increments, at 582, the saved pixel counter by one; andif counter value is, at 584, less than the saved number of pixels, theprocess steps 576-584 are repeated for each of the saved pixels. At theend of this process, all of the significant points and a hole area for acurrent HOI have been identified.

Returning to FIG. 11, the significant points for the HOI are classifiedinto a through hole or a blocked hole. The control 48 compares, at 482,the area of the HOI to a partial limit. If the area is greater than thepartial limit, the control 48 identifies, at 484, the HOI as a throughhole, for example, referring to FIG. 6B, holes 180 are through holes. Ifthe area is not greater than the partial limit, the HOI is identified,at 486, as a blocked hole. Referring to FIG. 6B, hole 176 is a fullyblocked hole; and hole 178 is a partially blocked hole and thus, not athrough hole. The hole status is displayed at 488 and saved to memory at489. The hole counter is incremented at 490 and compared to the totalnumber of holes at 492. If hole counter value is less than the totalnumber of holes, the steps 480-492 are repeated for each hole in thestored second image until the fourth data analysis method is completedas indicated at 494.

An exemplary embodiment of a fifth data analysis method is substantiallysimilar to the fourth data analysis method of FIG. 11 with oneexception. Referring to the analyze and classify HOI step 480 of FIG.11, in the calculation of the threshold in step 550 of FIG. 13, with thefourth data analysis method, n is equal to the number of holes orfeatures. However, in the fifth data analysis method, in the calculationof the threshold in step 550 of FIG. 13, n is equal to the total numberof pixels inside all of the holes 174 (FIG. 6B) within the current image170.

A sixth data analysis method is similar to the fourth data analysismethod except two IR images are analyzed just after the upstream airpressure is detected. The first image is labeled the “b_image”, and thesecond image is labeled the “a_image”. In an exemplary embodiment of thesixth data analysis method shown in FIG. 14, the control 48 executessteps 650-656 in a manner similar to that previously described withrespect to steps 450-456 of FIG. 11. Upon the control 48 determining, at656, that the upstream pressure is greater than 0.5 PSIG, the false flagis set true at 660; and, at 661, the current image and associated dataare saved as b_image. The control again iterates the process of steps650-656; and upon detecting the true flag at 658, the control 48 thensaves the current image and associated data as the a_image. In otherwords, the b_image and the a_image are the first two IR images after theupstream pressure has been detected.

The control 48 then, at 666, zeros the hole counter; and the standarddeviation of the a_image HOI is determined at 668 and saved at 670. Theexemplary embodiment of calculating a HOI standard deviation previouslyshown and described with respect to FIG. 12 may be used. The holecounter is incremented at 672; and if there are other holes in thea_image to analyze as determined at 674, the process of steps 666-674 isrepeated for each of the holes in the a_image. In a similar manner, byiterating process steps 667-675, a HOI standard deviation for each ofthe holes in the b-image is determined at 669 and stored at 671.

Thereafter, the control 48 calculates, at 676, an average of the HOIstandard deviations for all of the holes in the a_image; and the holecounter is zeroed at 678. The control 48 then performs, at 679, a HOIanalysis for the current HOI in the b_image. The exemplary embodiment ofa HOI analysis shown in FIG. 13 may be used; however, for this analysisthe threshold as determined at 550 of FIG. 13 is simply equal to theb_image HOI standard deviation determined at 669 of FIG. 14. Theremainder of the HOI analysis of FIG. 13 is substantially the same aspreviously described, so that when completed, a number of significantpoints or cold points within the HOI will be identified as will thetotal number of pixels in the HOI. Therefore, the difference between thenumber of significant points and the total number of pixels in the HOImay be determined and identified as the number of nonsignificant pointsor skin points.

The control 48 then determines a delta_b, at 681 of FIG. 14, which is adifference between an average temperature of all of the significantpoints and an average temperature of all of the skin points for thecurrent HOI in the b_image. In a similar manner, the control 48performs, at 683, a HOI analysis for the current HOI in the a_image andcalculates a delta_a at 685, which is a difference between an averagetemperature of all of the significant points and an average temperatureof all of the skin points for the current HOI in the a_image.

The control 48 then, at 687, subtracts the delta_a temperature from thedelta_b temperature. Since the delta_a temperature image was taken laterthan the delta_b temperature image after the application of the chilledupstream air, a lower delta_a temperature should indicate a presence ofa hole. In that event, the control 48 performs, at 680, a HOI analysisthat is substantially identical to the HOI analysis that was previouslydescribed with respect to FIG. 13. The result is a number of significantpoints in a current HOI that represents an area of the HOI. If thecontrol 48 determines, at 682, that the current HOI area is greater thana partial limit, the current HOI is identified, at 684, as a throughhole.

However, if at 682, the current HOI area is determined not to be greaterthan a partial limit, the current HOI is identified, at 686, as ablocked hole. Referring back to process step 687, a delta_a temperaturethat is higher than the delta_b temperature indicates that the flow ofchilled air is not detected and that there is no hole. Therefore, thecurrent HOI is identified, at 686, as a blocked hole. The control 48displays, at 688, the status of the current HOI, saves the hole statusat 689, and increments, at 690, the hole counter. If the hole counter isdetermined, at 692, to be less than the number of holes, the process ofsteps 679-692 is repeated for each of the holes in the a_image and theb_image.

A seventh data analysis method is also similar to the fourth dataanalysis method except that, again, two IR images are used. A first IRimage used was captured before the upstream air pressure was detected,and a second IR image used was captured just after the upstream airpressure was detected. The first image is called the “b_image”, and thesecond image is called the “a_image”. In an exemplary embodiment of theseventh data analysis method shown in FIG. 15, the control 48 executessteps 750-756 in a manner similar to that previously described withrespect to steps 450-456 of FIG. 11. Upon the control 48 determining, at756, that the upstream pressure is not activated, the false flag is settrue at 760; and, at 761, the current image and associated data aresaved as the b_image. The control again iterates the process of steps750-756; and upon detecting the upstream pressure is not less than 0.5PSIG, the control 48 then saves the current image and associated data asthe a_image.

The control 48 then, at 766, zeros the hole counter; and the standarddeviation of a difference between corresponding temperatures in thea_image and the b_image is determined at 768 and saved at 770. This isaccomplished by creating a difference array or grid of temperaturesequal in number to the number of temperatures in each of the a_image andthe b_image. However, in the difference array, the temperature or eacharray element is created by subtracting a temperature of a correspondingarray element in the a_image from a temperature of a corresponding arrayelement in the b_image. The exemplary embodiment of calculating a HOIstandard deviation shown and previously described with respect to FIG.12 may be applied to the difference array of temperatures to determine,at 768, an HOI standard deviation. That HOI standard deviation using thedifference array of temperatures is stored at 770. The hole counter isincremented at 772; and if there are other holes to analyze in thea_image and the b_image as determined at 774, the process of steps766-774 is repeated for each of the holes.

Thereafter, the control 48 calculates, at 776, an average of the HOIstandard deviations based on respective HOI standard deviations of thedifference array for all of the holes; and the hole counter is zeroed at778. The control 48 performs, at 780, a HOI analysis that issubstantially identical to the HOI analysis that was previouslydescribed with respect to FIG. 13. The result is a number of significantpoints in a current HOI and an area of the HOI. If the control 48determines, at 782, that the current HOI area is greater than a partiallimit, the current HOI is identified, at 784, as a through hole.However, if at 782, the current HOI area is determined not to be greaterthan a partial limit, the current HOI is identified, at 786, as ablocked hole. The control 48 displays the status of the current HOI at788, saves the hole status at 789, and increments the hole counter at790. If the hole counter is determined, at 792, to be less than thenumber of holes, the process of steps 780-792 is repeated for each ofthe holes in the difference array.

While the present invention has been illustrated by a description ofvarious embodiments and while these embodiments have been described inconsiderable detail, there is no intention to restrict or in any waylimit the scope of the appended claims to such detail. Additionaladvantages and modifications will readily appear to those skilled in theart. For example, while the hole inspection processes described hereinis directed to an application for inspecting features or holes in apart, in other applications, the described inspection processes can beused to inspect features on other parts, for example, fuel injectors,spray nozzles, combustors, stator blades, etc.

In the exemplary embodiments shown in FIGS. 2A and 8, gas dischargenozzles 112 and IR emitters 110 are mounted circumferentially next toeach other on a single ring around a lens 51 of an IR camera 50.However, in another alternative embodiment, the gas discharge nozzles112 may be mounted circumferentially on a first ring of a firstdiameter, and the IR emitters 110 may be mounted on a second ring of adifferent diameter. In a further embodiment, the gas discharge nozzles112 and IR emitters 110 may be mounted elsewhere on the robotic arm aslong as they are directed on the same feature(s) as the camera.

It should be noted that in the data analysis methods shown and describedherein, it is assumed that all of the features or holes have the sameshape and size. If an image frame contains features having differentshapes or sizes, then the first step of any analysis is to identifyregions of interest within the image frame that contain only featureshaving an identical shapes or sizes. Then the data analysis methodsshown and described herein may be implemented with the pixels withinthat region of interest as well as other regions of interest within theimage frame.

Therefore, the invention in its broadest aspects is not limited to thespecific details shown and described. Consequently, departures may bemade from the details described herein without departing from the spiritand scope of the claims which follow.

1. A method of inspecting a plurality of features extending from acavity within a structure to an outer surface of the structure byanalyzing saved thermal images of an area of the outer surface includingthe plurality of features, the thermal images having been captured andsaved at different times in response to first, heating the area of theouter surface, and thereafter, providing a cooled gas into the cavityand to the plurality of features, the method comprising: (a) identifyinga first thermal image captured after providing the cooled gas into thecavity, the first thermal image comprising an array of pixels of thearea of the outer surface including the plurality of features, whereineach pixel represents a temperature; (b) determining a plurality ofstandard deviations of temperatures, each of the plurality of standarddeviations being determined by temperatures represented by pixels withina boundary of a different one of the features; (c) determining anaverage of the plurality of standard deviations of temperatures; (d)determining a threshold temperature using the average of the pluralityof standard deviations of temperatures; (e) determining a minimumtemperature represented by pixels within boundaries of respective onesof the plurality of features; (f) identifying a number of significantpixels within the boundary of one of the features, each significantpixel representing a temperature less than a sum of the thresholdtemperature plus the minimum temperature, and the number of significantpixels representing an area of the one of the features allowing adesired flow of the cooled gas; (g) identifying the one of the featuresas a good feature in response to the number of significant pixels beinggreater than a predetermined number; and (h) iterating steps (f) through(g) for each of the plurality of features.
 2. The method of claim 1wherein determining a plurality of standard deviations comprises: (a)identifying pixels in the first thermal image within a boundary of oneof the features; (b) determining a standard deviation of temperaturesrepresented by the pixels within a boundary of the one of the features;and (c) iterating steps (a) and (b) for respective boundaries of each ofthe plurality of features in the first thermal image.
 3. The method ofclaim 1 wherein determining a minimum temperature comprises: (a)comparing a first minimum temperature of the temperatures represented bythe pixels within the boundary of the one of the features to apreviously determined minimum temperature represented pixels withinrespective boundaries of others of the plurality of features; and (b)saving as a new minimum temperature one of the first minimum temperatureand the previously determined minimum temperature representing a lowertemperature.
 4. The method of claim 1 wherein determining a thresholdtemperature comprises determining a threshold temperature according tothe following:threshold=√{square root over (k*avg_hoi_stdev*LOG(n))} Where k=0.001 to10, n=number of features in a thermal image.
 5. The method of claim 1wherein determining a threshold temperature comprises determining athreshold temperature according to the following:threshold=√{square root over (k*avg_hoi_stdev*LOG(n))} Where k=0.001 to10, n=total number of pixels within respective boundaries of theplurality of features.
 6. A method of inspecting a plurality of featuresextending from a cavity within a structure to an outer surface of thestructure by analyzing saved thermal images of an area of the outersurface including the plurality of features, the thermal images havingbeen captured and saved at different times in response to first, heatingthe area of the outer surface, and thereafter, providing a cooled gasinto the cavity and to the plurality of features, the method comprising:(a) identifying a first thermal image and a second thermal imagecaptured after providing the cooled gas into the cavity, the secondthermal image being captured later in time than the first thermal image,the first and the second thermal images comprising respective arrays ofpixels of an area of the outer surface that includes the plurality offeatures, wherein each pixel represents a temperature; (b) determining aplurality of first standard deviations of temperatures, each of theplurality of first standard deviations represented by pixels within aboundary of a different one of the features in the first thermal image;(c) determining a plurality of second standard deviations oftemperatures, each of the plurality of second standard deviationsrepresented by pixels within a boundary of a different one of thefeatures in the second thermal image; (d) identifying a feature as beingblocked in response to temperatures represented by pixels within aboundary of the feature in the second thermal image not being lower thantemperatures represented by pixels within a corresponding boundary ofthe feature in the first thermal image; and (e) identifying a feature inthe second thermal image as being good in response to a number ofsignificant pixels within a boundary of the feature representingtemperatures lower than surrounding pixels within the boundary of thefeature.
 7. The method of claim 6 wherein determining a plurality offirst standard deviations of temperatures further comprises identifyingpixels in the first thermal image within boundaries of respective onesof the plurality of features; and determining a plurality of secondstandard deviations of temperatures further comprises identifying pixelsin the second thermal image within boundaries of respective ones of theplurality of features.
 8. The method of claim 6 wherein identifying afeature as being blocked further comprises: (a) determining a firstthermal image minimum temperature represented by pixels withinboundaries of respective ones of the plurality of features in the firstthermal image; (b) determining for the first thermal image, a firstthermal image threshold temperature for the feature using a respectivefirst standard deviation of temperatures; (c) determining for the firstthermal image, a first average of first temperatures represented bypixels within the boundary of the feature, each of the firsttemperatures representing a temperature not greater than a sum of thefirst thermal image threshold temperature plus the first thermal imageminimum temperature; (d) determining for the first thermal image, asecond average of second temperatures represented by pixels within theboundary of the feature, each of the second temperatures representing atemperature that is greater than a sum of the first thermal imagethreshold temperature plus the first thermal image minimum temperature;(e) determining a first thermal image difference temperature bysubtracting the second average of second temperatures from the firstaverage of first temperatures; (f) determining a second thermal imageminimum temperature represented by pixels in within boundaries ofrespective ones of the plurality of features in the second thermalimage; (g) determining for the second thermal image, a second thermalimage threshold temperature for the feature using a respective secondstandard deviation of temperatures; (h) determining for the secondthermal image, a third average of third temperatures represented bypixels within the boundary of the feature, each of the thirdtemperatures representing a temperature not greater than a sum of thesecond thermal image threshold temperature plus the second thermal imageminimum temperature; (i) determining for the second thermal image, afourth average of fourth temperatures represented by pixels within theboundary of the feature, each of the fourth temperatures representing atemperature that is greater than a sum of the second thermal imagethreshold temperature plus the second thermal image minimum temperature;(j) determining a second thermal image difference temperature bysubtracting the fourth average of fourth temperatures from the thirdaverage of third temperatures; (k) determining a resulting differencetemperature by subtracting the second thermal image differencetemperature from the first thermal image difference temperature; and (l)identifying the feature as a blocked feature in response to theresulting difference temperature being greater than zero.
 9. The methodof claim 6 wherein identifying a feature as a good feature furthercomprises: (a) determining a second thermal image minimum temperaturerepresented by pixels within boundaries of the plurality of features inthe second thermal image; (b) determining an average of the plurality ofstandard deviations of temperatures in the second thermal image; (c)determining a second thermal image threshold temperature using theaverage of the plurality of standard deviations of temperatures in thesecond thermal image; (d) identifying a number of significant pixelswithin the boundary of the feature in the second thermal image, eachsignificant pixel representing a temperature less than a sum of thesecond thermal image threshold temperature plus the second thermal imageminimum temperature, and the number of significant pixels representingan area of the feature in the second thermal image allowing a desiredflow of the cooled gas; and (e) identifying the feature as a goodfeature in response to the number of significant pixels being greaterthan a predetermined number.
 10. The method of claim 9 whereindetermining a second thermal image minimum temperature comprises: (a)comparing a first temperature represented by a pixel within the boundaryof the feature to a previously determined minimum temperaturerepresented by pixels within respective boundaries of others of theplurality features; (b) saving as the second thermal image minimumtemperature one of the first temperature and the previously determinedminimum temperature representing a lower temperature; and (c) iteratingsteps (a) and (b) for each of the pixels within the boundary of thefeature.
 11. A method of inspecting a plurality of features extendingfrom a cavity within a structure to an outer surface of the structure byanalyzing saved thermal images of an area of the outer surface includingthe plurality of features, the thermal images having been captured andsaved at different times in response to first, heating the area of theouter surface, and thereafter, providing a cooled gas into the cavityand to the plurality of features, the method comprising: (a) identifyinga first thermal image and a second thermal image captured afterproviding the cooled gas into the cavity, the second thermal image beingcaptured later in time than the first thermal image, the first and thesecond thermal images comprising respective arrays of pixels of an areaof the outer surface that includes the plurality of features, whereineach pixel represents a temperature; (b) determining a first standarddeviation of temperatures represented by pixels within a boundary of oneof the features in the first thermal image; (c) determining a secondstandard deviation of temperatures represented by pixels within aboundary of the one of the features in the second thermal image; (d)identifying the one of the features as being a blocked feature inresponse to a temperature of the one of the features in the secondthermal image not being lower than a temperature of the one of thefeatures in the first thermal image; (e) identifying the one of thefeatures as a good feature in response to a number of significant pixelswithin the boundary of the one of the features in the second thermalimage representing temperatures lower than surrounding pixels within theboundary of the feature; and (f) iterating steps (b) through (e) foreach of the plurality of features.
 12. A method of inspecting aplurality of features extending from a cavity within a structure to anouter surface of the structure by analyzing saved thermal images of anarea of the outer surface including the plurality of features, thethermal images having been captured and saved at different times inresponse to first, heating the area of the outer surface, andthereafter, providing a cooled gas into the cavity and to the pluralityof features, the method comprising: (a) identifying a first thermalimage captured before providing the cooled gas into the cavity and asecond thermal image captured after providing the cooled gas into thecavity, the first and the second thermal images comprising respectivearrays of pixels of an area of the outer surface that includes theplurality of features, wherein each pixel represents a temperature; (b)creating a difference array of pixels, wherein each difference arraypixel element equals a difference in temperature between correspondingpixel elements of the first thermal image and the second thermal image;(c) determining a plurality of standard deviations of temperatures usingpixels in the difference array, each of the plurality of first standarddeviations being determined by temperatures represented by pixels withina boundary of a different one of the features; (d) determining anaverage of the plurality of standard deviations of temperatures; (e)determining a threshold temperature using the average of the pluralityof standard deviations of temperatures; (f) determining a minimumtemperature represented by pixels in the difference array withinboundaries of respective ones of the plurality of features; (g)identifying a number of significant pixels within a boundary of afeature, each significant pixel representing a temperature less than asum of the threshold temperature plus the minimum temperature, and thenumber of significant pixels representing an area of the featureallowing a desired flow of the cooled gas; and (h) identifying thefeature as a good feature in response to the number of significantpixels being greater than a predetermined number.
 13. The method ofclaim 12 wherein determining a plurality of standard deviations oftemperatures further comprises identifying pixels in the first thermalimage within boundaries of respective ones of the plurality of features.14. The method of claim 12 wherein creating a difference array of pixelsfurther comprises determining a temperature for each difference arraypixel element by subtracting a temperature of a corresponding arrayelement in the second thermal image from a temperature of acorresponding array element in the first thermal image.
 15. The methodof claim 12 wherein determining a minimum temperature comprises: (a)comparing a first temperature represented by a pixel within the boundaryof the feature to a previously determined minimum temperaturerepresented by pixels within respective boundaries of others of theplurality features; (b) saving as the minimum temperature one of thefirst temperature and the previously determined minimum temperaturerepresenting a lower temperature; and (c) iterating steps (a) and (b)for each of the pixels within the boundary of the feature.